Rasa: Open Source Language Understanding and Dialogue Management
This work provides tools for non-specialist software developers to implement conversational AI, but it is incremental as it packages existing methods into accessible libraries.
The authors introduced Rasa NLU and Rasa Core, open-source Python libraries for building conversational software, aiming to make machine-learning-based dialogue management and language understanding accessible to non-specialist developers with ease of use and minimal initial training data.
We introduce a pair of tools, Rasa NLU and Rasa Core, which are open source python libraries for building conversational software. Their purpose is to make machine-learning based dialogue management and language understanding accessible to non-specialist software developers. In terms of design philosophy, we aim for ease of use, and bootstrapping from minimal (or no) initial training data. Both packages are extensively documented and ship with a comprehensive suite of tests. The code is available at https://github.com/RasaHQ/